Examples of FuzzyKMeansClusteringPolicy

org.apache.mahout.clustering.FuzzyKMeansClusteringPolicy
This is a probability-weighted clustering policy, suitable for fuzzy k-means clustering
org.apache.mahout.clustering.iterator.FuzzyKMeansClusteringPolicy
This is a probability-weighted clustering policy, suitable for fuzzy k-means clustering

Examples of org.apache.mahout.clustering.iterator.FuzzyKMeansClusteringPolicy

    List<Cluster> initialClusters = Lists.newArrayList();
    int id = 0;
    for (Vector point : points) {
      initialClusters.add(new SoftCluster(point, id++, measure));
    }
    ClusterClassifier prior = new ClusterClassifier(initialClusters, new FuzzyKMeansClusteringPolicy(m, threshold));
    Path priorPath = new Path(output, "classifier-0");
    prior.writeToSeqFiles(priorPath);
    
    new ClusterIterator().iterateSeq(conf, samples, priorPath, output, maxIterations);
    loadClustersWritable(output);

View Full Code Here

Examples of org.apache.mahout.clustering.iterator.FuzzyKMeansClusteringPolicy

    if (clusters.isEmpty()) {
      throw new IllegalStateException("No input clusters found in " + clustersIn + ". Check your -c argument.");
    }
    
    Path priorClustersPath = new Path(output, Cluster.INITIAL_CLUSTERS_DIR);   
    ClusteringPolicy policy = new FuzzyKMeansClusteringPolicy(m, convergenceDelta);
    ClusterClassifier prior = new ClusterClassifier(clusters, policy);
    prior.writeToSeqFiles(priorClustersPath);
    
    if (runSequential) {
      ClusterIterator.iterateSeq(conf, input, priorClustersPath, output, maxIterations);

View Full Code Here

Examples of org.apache.mahout.clustering.iterator.FuzzyKMeansClusteringPolicy

                                 boolean emitMostLikely,
                                 double threshold,
                                 boolean runSequential)
    throws IOException, ClassNotFoundException, InterruptedException {
    
    ClusterClassifier.writePolicy(new FuzzyKMeansClusteringPolicy(m, convergenceDelta), clustersIn);
    ClusterClassificationDriver.run(conf, input, output, new Path(output, PathDirectory.CLUSTERED_POINTS_DIRECTORY),
        threshold, emitMostLikely, runSequential);
  }

View Full Code Here

0 1

TOP

All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.